The mechanical behaviour of metallic materials is governed by properties of the underlying microstructure. Understanding and predicting the structure-property relation is central to experimental and computational materials science. Over the last decades a large number of different simulation methods on various time and length scales has evolved. At the same time, advanced experimental characterization methods with high resolutions are able to reveal a rich variety of details about microstructural features. This offers a number of interesting possibilities, e.g. to use experiments for validating computational results on a microstructural level, or to use microstructure data from a 'lower scale' method (e.g. atomistics) - directly or indirectly - as input or for validation purposes for simulation method on larger scales. Up to date, however, systematic and detailed methodologies for comparing and validating data from different methods are still lagging behind.
In this presentation we introduce our D2C (=discrete to continuous) approach , which is a novel 'language' for computationally characterizing dislocation microstructures in a multiscale approach. This data format allows to directly compare dislocation microstructures from, e.g., MD simulations, TEM microscopy or tomography, continuum or DDD simulations. We show how our D2C framework can be used to perform ensemble averages of statistically equivalent simulations/experiments. This is ideal for validation and data mining of in particular discrete methods (MD or DDD simulations as well as specialized experiments), whose microstructural data are often not easily accessible. To demonstrate this, we present first results from using D2C together with DDD data to identify energetical expressions that can then be used as input for continuum simulations.
 S. Sandfeld and G. Po, Microstructural comparison of the kinematics of discrete and continuum dislocations models, Modelling and Simulation in Materials Science and Engineering, Volume 23, Number 8, 2015